@inproceedings{65474, author = {{Rook, Jeroen and López-Ibáñez, Manuel}}, booktitle = {{Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO 2025, NH Malaga Hotel, Malaga, Spain, July 14-18, 2025}}, editor = {{Filipic, Bogdan}}, pages = {{1617–1642}}, publisher = {{ACM}}, title = {{{Advanced Use of Automatic Algorithm Configuration: Single- and Multi-Objective Approaches}}}, doi = {{10.1145/3712255.3716537}}, year = {{2025}}, } @unpublished{61778, abstract = {{Understanding the entanglement structure of local Hamiltonian ground spaces is a physically motivated problem, with applications ranging from tensor network design to quantum error-correcting codes. To this end, we study the complexity of estimating ground state entanglement, and more generally entropy estimation for low energy states and Gibbs states. We find, in particular, that the classes qq-QAM [Kobayashi, le Gall, Nishimura, SICOMP 2019] (a quantum analogue of public-coin AM) and QMA(2) (QMA with unentangled proofs) play a crucial role for such problems, showing: (1) Detecting a high-entanglement ground state is qq-QAM-complete, (2) computing an additive error approximation to the Helmholtz free energy (equivalently, a multiplicative error approximation to the partition function) is in qq-QAM, (3) detecting a low-entanglement ground state is QMA(2)-hard, and (4) detecting low energy states which are close to product states can range from QMA-complete to QMA(2)-complete. Our results make progress on an open question of [Bravyi, Chowdhury, Gosset and Wocjan, Nature Physics 2022] on free energy, and yield the first QMA(2)-complete Hamiltonian problem using local Hamiltonians (cf. the sparse QMA(2)-complete Hamiltonian problem of [Chailloux, Sattath, CCC 2012]).}}, author = {{Gharibian, Sevag and Kamminga, Jonas}}, booktitle = {{arXiv:2510.06796}}, title = {{{On the complexity of estimating ground state entanglement and free energy}}}, year = {{2025}}, } @inproceedings{65618, author = {{Bröker, Mika and Menzel, Johannes and Plessl, Christian}}, booktitle = {{Proceedings of the 15th International Symposium on Highly Efficient Accelerators and Reconfigurable Technologies}}, publisher = {{ACM}}, title = {{{Evaluating the Strong Scaling Potential of AI Engines for Molecular Dynamics Simulations}}}, doi = {{10.1145/3728179.3728187}}, year = {{2025}}, } @inproceedings{50272, abstract = {{Despite the fundamental role the Quantum Satisfiability (QSAT) problem has played in quantum complexity theory, a central question remains open: At which local dimension does the complexity of QSAT transition from "easy" to "hard"? Here, we study QSAT with each constraint acting on a $k$-dimensional and $l$-dimensional qudit pair, denoted $(k,l)$-QSAT. Our first main result shows that, surprisingly, QSAT on qubits can remain $\mathsf{QMA}_1$-hard, in that $(2,5)$-QSAT is $\mathsf{QMA}_1$-complete. In contrast, $2$-SAT on qubits is well-known to be poly-time solvable [Bravyi, 2006]. Our second main result proves that $(3,d)$-QSAT on the 1D line with $d\in O(1)$ is also $\mathsf{QMA}_1$-hard. Finally, we initiate the study of 1D $(2,d)$-QSAT by giving a frustration-free 1D Hamiltonian with a unique, entangled ground state. Our first result uses a direct embedding, combining a novel clock construction with the 2D circuit-to-Hamiltonian construction of [Gosset, Nagaj, 2013]. Of note is a new simplified and analytic proof for the latter (as opposed to a partially numeric proof in [GN13]). This exploits Unitary Labelled Graphs [Bausch, Cubitt, Ozols, 2017] together with a new "Nullspace Connection Lemma", allowing us to break low energy analyses into small patches of projectors, and to improve the soundness analysis of [GN13] from $\Omega(1/T^6)$ to $\Omega(1/T^2)$, for $T$ the number of gates. Our second result goes via black-box reduction: Given an arbitrary 1D Hamiltonian $H$ on $d'$-dimensional qudits, we show how to embed it into an effective null-space of a 1D $(3,d)$-QSAT instance, for $d\in O(1)$. Our approach may be viewed as a weaker notion of "simulation" (\`a la [Bravyi, Hastings 2017], [Cubitt, Montanaro, Piddock 2018]). As far as we are aware, this gives the first "black-box simulation"-based $\mathsf{QMA}_1$-hardness result, i.e. for frustration-free Hamiltonians.}}, author = {{Rudolph, Dorian and Gharibian, Sevag and Nagaj, Daniel}}, booktitle = {{16th Innovations in Theoretical Computer Science (ITCS)}}, number = {{85}}, pages = {{1--24}}, title = {{{Quantum 2-SAT on low dimensional systems is $\mathsf{QMA}_1$-complete: Direct embeddings and black-box simulation}}}, doi = {{10.4230/LIPIcs.ITCS.2025.85}}, volume = {{325}}, year = {{2025}}, } @article{55037, abstract = {{Estimating ground state energies of many-body Hamiltonians is a central task in many areas of quantum physics. In this work, we give quantum algorithms which, given any $k$-body Hamiltonian $H$, compute an estimate for the ground state energy and prepare a quantum state achieving said energy, respectively. Specifically, for any $\varepsilon>0$, our algorithms return, with high probability, an estimate of the ground state energy of $H$ within additive error $\varepsilon M$, or a quantum state with the corresponding energy. Here, $M$ is the total strength of all interaction terms, which in general is extensive in the system size. Our approach makes no assumptions about the geometry or spatial locality of interaction terms of the input Hamiltonian and thus handles even long-range or all-to-all interactions, such as in quantum chemistry, where lattice-based techniques break down. In this fully general setting, the runtime of our algorithms scales as $2^{cn/2}$ for $c<1$, yielding the first quantum algorithms for low-energy estimation breaking the natural bound based on Grover search. The core of our approach is remarkably simple, and relies on showing that any $k$-body Hamiltonian has a low-energy subspace of exponential dimension.}}, author = {{Buhrman, Harry and Gharibian, Sevag and Landau, Zeph and Gall, François Le and Schuch, Norbert and Tamaki, Suguru}}, journal = {{Physical Review Letters}}, pages = {{030601}}, title = {{{Beating Grover search for low-energy estimation and state preparation}}}, doi = {{10.1103/29qw-bssx}}, volume = {{135}}, year = {{2025}}, } @unpublished{61776, abstract = {{We investigate the role of energy, i.e. average photon number, as a resource in the computational complexity of bosonic systems. We show three sets of results: (1. Energy growth rates) There exist bosonic gate sets which increase energy incredibly rapidly, obtaining e.g. infinite energy in finite/constant time. We prove these high energies can make computing properties of bosonic computations, such as deciding whether a given computation will attain infinite energy, extremely difficult, formally undecidable. (2. Lower bounds on computational power) More energy ``='' more computational power. For example, certain gate sets allow poly-time bosonic computations to simulate PTOWER, the set of deterministic computations whose runtime scales as a tower of exponentials with polynomial height. Even just exponential energy and $O(1)$ modes suffice to simulate NP, which, importantly, is a setup similar to that of the recent bosonic factoring algorithm of [Brenner, Caha, Coiteux-Roy and Koenig (2024)]. For simpler gate sets, we show an energy hierarchy theorem. (3. Upper bounds on computational power) Bosonic computations with polynomial energy can be simulated in BQP, ``physical'' bosonic computations with arbitrary finite energy are decidable, and the gate set consisting of Gaussian gates and the cubic phase gate can be simulated in PP, with exponential bound on energy, improving upon the previous PSPACE upper bound. Finally, combining upper and lower bounds yields no-go theorems for a continuous-variable Solovay--Kitaev theorem for gate sets such as the Gaussian and cubic phase gates.}}, author = {{Chabaud, Ulysse and Gharibian, Sevag and Mehraban, Saeed and Motamedi, Arsalan and Naeij, Hamid Reza and Rudolph, Dorian and Sambrani, Dhruva}}, booktitle = {{arXiv:2510.08545}}, title = {{{Energy, Bosons and Computational Complexity}}}, year = {{2025}}, } @unpublished{60432, abstract = {{The Quantum k-SAT problem is the quantum generalization of the k-SAT problem. It is the problem whether a given local Hamiltonian is frustration-free. Frustration-free means that the ground state of the k-local Hamiltonian minimizes the energy of every local interaction term simultaneously. This is a central question in quantum physics and a canonical QMA_1-complete problem. The Quantum k-SAT problem is not as well studied as the classical k-SAT problem in terms of special tractable cases, approximation algorithms and parameterized complexity. In this paper, we will give a graph-theoretic study of the Quantum k-SAT problem with the structures core and radius. These hypergraph structures are important to solve the Quantum k-SAT problem. We can solve a Quantum k-SAT instance in polynomial time if the derived hypergraph has a core of size n-m+a, where a is a constant, and the radius is at most logarithmic. If it exists, we can find a core of size n-m+a with the best possible radius in polynomial time, whereas finding a general minimum core with minimal radius is NP-hard.}}, author = {{Kremer, Simon-Luca and Rudolph, Dorian and Gharibian, Sevag}}, booktitle = {{arXiv:2506.17066}}, title = {{{Quantum k-SAT Related Hypergraph Problems}}}, year = {{2025}}, } @inproceedings{61256, author = {{Illian, Marvin and Luchterhandt, Björn and Wang, Lin}}, booktitle = {{Proceedings of the 20th Workshop on Mobility in the Evolving Internet Architecture (MobiArch)}}, location = {{Hong Kong, China}}, title = {{{Band Switching for Mobile Energy Optimization in 5G Networks and Beyond}}}, doi = {{10.1145/3737897.3767294}}, year = {{2025}}, } @inproceedings{65734, author = {{Kamdem Teyou, Louis Mozart and Friedrichs, Luke and Kouagou, N'Dah Jean and Demir, Caglar and Mahmood, Yasir and Heindorf, Stefan and Ngonga Ngomo, Axel-Cyrille}}, location = {{Dayton-USA}}, title = {{{Neural Reasoning for Robust Instance Retrieval in SHOIQ}}}, doi = {{https://doi.org/10.1145/3731443.377134}}, year = {{2025}}, } @inproceedings{61986, author = {{Rasor, Anja and Vehmeyer, Julia Marie and Kirchberg, Lisa and Scholtysik, Michel and Koldewey, Christian and Dumitrescu, Roman}}, booktitle = {{Procedia CIRP}}, issn = {{2212-8271}}, pages = {{972--977}}, publisher = {{Elsevier BV}}, title = {{{Key performance indicator system for evaluating the circular economy along the value chain}}}, doi = {{10.1016/j.procir.2025.01.084}}, volume = {{135}}, year = {{2025}}, } @inproceedings{61955, author = {{Koldewey, Christian and Rohde, Malte Nick and Strobel, Gero and Vehmeyer, Julia Marie and Fichtler, Timm and Dumitrescu, Roman}}, booktitle = {{2025 IEEE International Conference on Engineering, Technology, and Innovation (ICE/ITMC)}}, publisher = {{IEEE}}, title = {{{Embedding Generative AI into Products – 10 Design Principles for Building Intelligent Systems}}}, doi = {{10.1109/ice/itmc65658.2025.11106522}}, year = {{2025}}, } @inproceedings{66098, author = {{Lütke Stockdiek, Janina and Grimme, Britta and Griesbach, Marie and Grimme, Christian}}, booktitle = {{International Artificial Intelligence Symposium}}, pages = {{432–447}}, title = {{{Out of Order: On the Importance of Word Positions in Explaining Text Classification}}}, year = {{2025}}, } @inproceedings{58801, abstract = {{Iran employs one of the most prominent Internet censors in the world. An important part of Iran’s censorship apparatus is its analysis of unencrypted protocols such as HTTP and DNS. During routine evaluations of Iran’s HTTP and DNS censorship, we noticed several properties we believe to be unknown today. For instance, we found injections of correct static IPs for some domains such as google.com on the DNS level, unclear HTTP version parsing, and correlations between DNS and HTTP censorship. In this paper, we present our findings to the community and discuss possible takeaways for affected people and the censorship circumvention community. As some of our findings left us bewildered, we hope to ignite a discussion about Iran’s censorship behavior. We aim to use the discussion of our work to execute a thorough analysis and explanation of Iran’s censorship behavior in the future.}}, author = {{Lange, Felix and Niere, Niklas and von Niessen, Jonathan and Suermann, Dennis and Heitmann, Nico and Somorovsky, Juraj}}, booktitle = {{Proceedings on Privacy Enhancing Technologies}}, location = {{Virtual}}, title = {{{I(ra)nconsistencies: Novel Insights into Iran’s Censorship}}}, year = {{2025}}, } @inproceedings{48632, abstract = {{Digital Servitization is one of the significant trends affecting the manufacturing industry. Companies try to tackle challenges regarding their differentiation and profitability using digital services. One specific type of digital services are smart services, which are digital services built on data from smart products. Introducing these kinds of offerings into the portfolio of manufacturing companies is not trivial. Moreover, they require conscious action to align all relevant capabilities to realize the respective business goals. However, what capabilities are generally relevant for smart services remains opaque. We conducted a systematic literature review to identify them and extended the results through an interview study. Our analysis results in 78 capabilities clustered among 12 principles and six dimensions. These results provide significant support for the smart service transformation of manufacturing companies and for structuring the research field of smart services.}}, author = {{Koldewey, Christian and Fichtler, Timm and Scholtysik, Michel and Biehler, Jan and Schreiner, Nick and Sommer, Franziska and Schacht, Maximilian and Kaufmann, Jonas and Rabe, Martin and Sedlmeier, Joachim and Dumitrescu, Roman}}, keywords = {{Digital Servitization, Transformation, Capabilities, Maturity, Smart Services}}, location = {{Hawaii}}, title = {{{Exploring Capabilities for the Smart Service Transformation in Manufacturing: Insights from Theory and Practice}}}, year = {{2024}}, } @inproceedings{49354, author = {{Afroze, Lameya and Merkelbach, Silke and von Enzberg, Sebastian and Dumitrescu, Roman}}, booktitle = {{ML4CPS 2023}}, location = {{Hamburg}}, title = {{{Domain Knowledge Injection Guidance for Predictive Maintenance}}}, year = {{2024}}, } @inproceedings{49364, author = {{Scholtysik, Michel and Rohde, Malte and Koldewey, Christian and Dumitrescu, Roman}}, title = {{{Business strategy taxonomy and solution patterns for the circular economy}}}, year = {{2024}}, } @unpublished{51160, abstract = {{We rigorously derive novel and sharp finite-data error bounds for highly sample-efficient Extended Dynamic Mode Decomposition (EDMD) for both i.i.d. and ergodic sampling. In particular, we show all results in a very general setting removing most of the typically imposed assumptions such that, among others, discrete- and continuous-time stochastic processes as well as nonlinear partial differential equations are contained in the considered system class. Besides showing an exponential rate for i.i.d. sampling, we prove, to the best of our knowledge, the first superlinear convergence rates for ergodic sampling of deterministic systems. We verify sharpness of the derived error bounds by conducting numerical simulations for highly-complex applications from molecular dynamics and chaotic flame propagation.}}, author = {{Philipp, Friedrich M. and Schaller, Manuel and Boshoff, Septimus and Peitz, Sebastian and Nüske, Feliks and Worthmann, Karl}}, booktitle = {{arXiv:2402.02494}}, title = {{{Extended Dynamic Mode Decomposition: Sharp bounds on the sample efficiency}}}, year = {{2024}}, } @article{46019, abstract = {{We derive efficient algorithms to compute weakly Pareto optimal solutions for smooth, convex and unconstrained multiobjective optimization problems in general Hilbert spaces. To this end, we define a novel inertial gradient-like dynamical system in the multiobjective setting, which trajectories converge weakly to Pareto optimal solutions. Discretization of this system yields an inertial multiobjective algorithm which generates sequences that converge weakly to Pareto optimal solutions. We employ Nesterov acceleration to define an algorithm with an improved convergence rate compared to the plain multiobjective steepest descent method (Algorithm 1). A further improvement in terms of efficiency is achieved by avoiding the solution of a quadratic subproblem to compute a common step direction for all objective functions, which is usually required in first-order methods. Using a different discretization of our inertial gradient-like dynamical system, we obtain an accelerated multiobjective gradient method that does not require the solution of a subproblem in each step (Algorithm 2). While this algorithm does not converge in general, it yields good results on test problems while being faster than standard steepest descent.}}, author = {{Sonntag, Konstantin and Peitz, Sebastian}}, journal = {{Journal of Optimization Theory and Applications}}, publisher = {{Springer}}, title = {{{Fast Multiobjective Gradient Methods with Nesterov Acceleration via Inertial Gradient-Like Systems}}}, doi = {{10.1007/s10957-024-02389-3}}, year = {{2024}}, } @unpublished{51334, abstract = {{The efficient optimization method for locally Lipschitz continuous multiobjective optimization problems from [1] is extended from finite-dimensional problems to general Hilbert spaces. The method iteratively computes Pareto critical points, where in each iteration, an approximation of the subdifferential is computed in an efficient manner and then used to compute a common descent direction for all objective functions. To prove convergence, we present some new optimality results for nonsmooth multiobjective optimization problems in Hilbert spaces. Using these, we can show that every accumulation point of the sequence generated by our algorithm is Pareto critical under common assumptions. Computational efficiency for finding Pareto critical points is numerically demonstrated for multiobjective optimal control of an obstacle problem.}}, author = {{Sonntag, Konstantin and Gebken, Bennet and Müller, Georg and Peitz, Sebastian and Volkwein, Stefan}}, booktitle = {{arXiv:2402.06376}}, title = {{{A Descent Method for Nonsmooth Multiobjective Optimization in Hilbert Spaces}}}, year = {{2024}}, } @article{40171, abstract = {{We present a convolutional framework which significantly reduces the complexity and thus, the computational effort for distributed reinforcement learning control of dynamical systems governed by partial differential equations (PDEs). Exploiting translational equivariances, the high-dimensional distributed control problem can be transformed into a multi-agent control problem with many identical, uncoupled agents. Furthermore, using the fact that information is transported with finite velocity in many cases, the dimension of the agents’ environment can be drastically reduced using a convolution operation over the state space of the PDE, by which we effectively tackle the curse of dimensionality otherwise present in deep reinforcement learning. In this setting, the complexity can be flexibly adjusted via the kernel width or by using a stride greater than one (meaning that we do not place an actuator at each sensor location). Moreover, scaling from smaller to larger domains – or the transfer between different domains – becomes a straightforward task requiring little effort. We demonstrate the performance of the proposed framework using several PDE examples with increasing complexity, where stabilization is achieved by training a low-dimensional deep deterministic policy gradient agent using minimal computing resources.}}, author = {{Peitz, Sebastian and Stenner, Jan and Chidananda, Vikas and Wallscheid, Oliver and Brunton, Steven L. and Taira, Kunihiko}}, journal = {{Physica D: Nonlinear Phenomena}}, pages = {{134096}}, publisher = {{Elsevier}}, title = {{{Distributed Control of Partial Differential Equations Using Convolutional Reinforcement Learning}}}, doi = {{10.1016/j.physd.2024.134096}}, volume = {{461}}, year = {{2024}}, }